1. Field of Invention
This invention is in the field of automatic target recognition applied to a radar image.
2. Description of the Related Art
An important function of a radar system, whether a Real Beam type, Synthetic Aperture (SAR) or Interferometric SAR is to detect a target as well as identify it. Radar target detection and identification have been proven necessary in military surveillance, reconnaissance, and combat missions. The detection and identification of targets provide real-time assessment of the number and the locations of targets of interest.
One method of target detection and identification is to process the image acquired by the radar using, for example, Synthetic Aperture Radar (SAR) technology. By processing a SAR generated image, the features of a target can be extracted and matched to a database for identification.
The general principle behind SAR is to obtain high resolution images by coherently combining the amplitude and phase information of separate radar returns from a plurality of sequentially transmitted pulses from a relatively small antenna on a moving platform. The returns from the plurality of pulses transmitted during a SAR image, when coherently combined and processed, result in image quality comparable to a longer antenna, corresponding approximately to the synthetic “length” traveled by the antenna during the acquisition of the image.
High resolution SAR maps are obtained by coherently combining return signals reflected from transmitted pulses in the cross range direction from radar platform movement. However, formation of focused SAR images or maps requires accurate information on platform position and velocity to shift and focus the received radar returns over the duration of the image acquisition time, the array length, so as to have a useful, phase adjusted combination of pulse returns from multiple pulses transmitted at different times from different radar positions. The process of aligning pulses in time and space for coherent integration is referred to as motion compensation, and is usually performed with the raw radar data, at the early stage of the image formation process.
The plurality of returns forming the image generated by the transmitted pulses along a known path of the platform make up an array length. During the array length, amplitude as well as phase information (in phase (I) and quadrature(Q) components) returned from reception of returns from each transmitted pulse, for each of many range bins, is preserved. The SAR image is formed and focused from the coherent combination of the amplitude and phase of return(s) within each range bin, motion compensated (phase adjusted) for spatial displacement of the moving platform during the acquisition of the returns for the duration of the array length.
One aspect of achieving coherent integration of pulses into one SAR image is the need for some form of inertial navigation/ground positioning satellite system (INS/GPS) to indicate the spatial and time coordinates of each transmitted and received (or reflected) pulse. These time and space coordinates of radar returns need to be known to a relatively high accuracy, typically in fractions of a wavelength, to arrive at a clear, focused, un-smeared image. Sometimes the alignment of pulses using the INS/CPS is imperfect, especially towards the edge of the image, introducing “snow” or a grainy character into the SAR image, making it difficult to discern target outline from its background.
It is this grainy character that tends to obfuscate a SAR image thus requiring robust algorithms to extract a target from the SAR image as well as identifying it. The radar image varies from radar to radar depending on the accuracy of the particular INS/CPS, the position of the target within the imaging area, instantaneous operating frequency, as well as glint/fading and target fluctuations. Thus, unlike photographic images, target detection and identification requires a robust approach capable of compensating for characteristics specific to a particular radar system, its operation and type of target being imaged and identified.
Attempts have been made towards target identification extracted from radar images. For example, U.S. Pat. No. 6,295,373 to Abhijit Mahalanobis et al, incorporated herein in its entirety, including all references, describes a method and apparatus for detecting a pattern within an image. Similarly, U.S. Pat. No. 5,947,413, also incorporated herein in its entirety, including references, uses correlation filters for target re-acquisition in trackers.
Another example, J. Wissinger, et. al., in MSTAR's Extensible Search Engine and Model-Based Inferencing Toolkit, SPIE 13th Annual International Symposium on AeroSene, Algorithms for SAR Imagery VI,incorporated herein in its entirety, including all references, rely on models to implement an algorithm for target identification. During operation, all targets under consideration are forced into one of the known target classes. There is no mechanism to adapt for an unknown target. Thus a high false alarm rate is encountered.
Similarly, J. De Bonet, P. Viola, and J. Fisher, in Flexible Histograms: A Multiresolution Target Discrimination Model SPIE Proceedings, 1998, rely only on multiscale features of targets. Again, this yields a relatively high false alarm rate.
Because of above limitations of the prior art, high false alarm rates are encountered, limiting the utility of an imaging and target detection radar.